The present invention is directed generally to a method and apparatus for controlling a setpoint for a process control variable, and more particularly, to a method and apparatus utilizing a dynamic reconciliation technique.
Numerous types of controllers and control systems are known which take advantage of process models for controlling a process parameter. In one type a simple dynamic relationship is assumed between the manipulated process variable and the controlled process parameter. The known value of the manipulated variable is then used with the model to estimate the controlled process parameter. The difference or bias between the predicted value of the controlled parameter and the measured value of that parameter is used to adjust the manipulated process variable to move the controlled process parameter to the desired value. This technique is called "Internal Model Control" and was described by C. E. Garcia and M. Morari in IEC. Proc. Des. and Dev., Volume 21 in 1982.
Another technique postulates a simple dynamic relationship between a process parameter which can be easily measured, such as a temperature, and the process parameter to be controlled, such as a concentration, which is more difficult to measure. The model and the easily measured process parameter are then used to estimate the controlled process parameter. Once again the value of the controlled process parameter predicted by the model is compared with the measured value of the controlled process parameter and a difference or bias is calculated. This bias is then used to adjust the manipulated process variable to move the controlled process parameter to its desired value. This technique is called Dynamic Reconciliation and was described in an article by Robert V. Bartman entitled "Dual Composition Control in a C.sub.3 /C.sub.4 Splitter" appearing in the September 1981 issue of CEP.
An alternative approach is to use a material or energy balance model to estimate the controlled process parameter. As in the above techniques the difference between the model estimate of the controlled process parameter and the measured value of the controlled process parameter is used to adjust the manipulated variable to move the controlled process parameter to its desired value. This is the approach described herein.